High-power lasers are vital for particle acceleration, imaging, fusion and materials processing, requiring precise control and high-energy delivery. Laser plasma accelerators (LPAs) demand laser positional stability at focus to ensure consistent electron beams in applications such as X-ray free-electron lasers and high-energy colliders. Achieving this stability is especially challenging for the low-repetition-rate lasers in current LPAs. We present a machine learning method that predicts and corrects laser pointing instabilities in real-time using a high-frequency pilot beam. By preemptively adjusting a correction mirror, this approach overcomes traditional feedback limits. Demonstrated on the BELLA petawatt laser operating at the terawatt level (30 mJ amplification), our method achieved root mean square pointing stabilization of 0.34 and 0.59 $\unicode{x3bc} \mathrm{rad}$ in the x and y directions, reducing jitter by 65% and 47%, respectively. This is the first successful application of predictive control for shot-to-shot stabilization in low-repetition-rate laser systems, paving the way for full-energy petawatt lasers and transformative advances across science, industry and security.

The next generation of high-power lasers enables repetition of experiments at orders of magnitude higher frequency than what was possible using the prior generation. Facilities requiring human intervention between laser repetitions need to adapt in order to keep pace with the new laser technology. A distributed networked control system can enable laboratory-wide automation and feedback control loops. These higher-repetition-rate experiments will create enormous quantities of data. A consistent approach to managing data can increase data accessibility, reduce repetitive data-software development and mitigate poorly organized metadata. An opportunity arises to share knowledge of improvements to control and data infrastructure currently being undertaken. We compare platforms and approaches to state-of-the-art control systems and data management at high-power laser facilities, and we illustrate these topics with case studies from our community.

Controlling the delivery of multi-terawatt and petawatt laser pulses to final focus, both in position and angle, is critical to many laser applications such as optical guiding, laser–plasma acceleration, and laser-produced secondary radiation. We present an online, non-destructive laser diagnostic, capable of measuring the transverse position and pointing angle at focus. The diagnostic is based on a unique double-surface-coated wedged-mirror design for the final steering optic in the laser line, producing a witness beam highly correlated with the main beam. By propagating low-power kilohertz pulses to focus, we observed spectra of focus position and pointing angle fluctuations dominated by frequencies below 70 Hz. The setup was also used to characterize the excellent position and pointing angle correlation of the 1 Hz high-power laser pulses to this low-power kilohertz pulse train, opening a promising path to fast non-perturbative feedback concepts even on few-hertz-class high-power laser systems.